LINE 4: INNOVATIVE TECHNOLOGIES IN DIAGNOSTICS AND THERAPIES AND IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE
This research line promotes the advancement of technological innovation which aim to define new diagnostic technologies and novel combined therapeutic approaches which facilitate the execution and participation in interventional clinical trials. Moreover, the development and use of digital tools capable of integrating and analyzing the large amount of clinical and research data from multiple sources for the purpose of evaluating and verifying the outcomes over time of cancer therapies in the real world (real world evidences) represent an additional field of this line’s application. Improving prognosis for oncology patients affected with both higher-incidence and rare cancers, for which IRE has acquired special expertise over time and a role in the European EURACAN network, through the synergistic integration of our diagnostic and the therapeutic capabilities. Through technological advances in biomolecular research, imaging with the integration of radiomics and radiogenomics data, minimally invasive surgery, radiotherapy, and with the use of molecular-targeted therapies in cancer, we have succeeded in increasingly using and making personalized therapies based on the individual characteristics of patients a reality. Radiomics is a current field of interest that is increasingly gaining momentum in oncology. The possibility of extracting a large amount of numerical data from images of Computed Tomography, Magnetic Resonance Imaging, Mammography, PET-CT, or Ultrasound allows an accurate and noninvasive characterization of tissues and neoplasms, which cannot be detected by visual imaging alone. However, this is possible by following rigorous standards, that have recently defined by international guidelines, to render the complex methodology of radiomic analysis reproducible and robust. Additional integration of data expressing the molecular and genomic characteristics of tissues allows to further enhance these diagnostic tools, with the goal of building an integrated dataset of radiogenomic information useful for creating prognostic-predictive models to be used in the decision making process in clinical practice. Of paramount importance in this context is the use of digital and artificial intelligence tools for the integration and interpretation of data (big data) from multiple sources (public databases, electronic patient records, data from clinical and translational diagnostics and research, and advanced preclinical models), and the creation of these models requires establishing data centers and adopting business intelligence methods. Since there is no international consensus on the use of artificial intelligence tools to be used in building classification or regression models yet, one of the objectives of this line of research is also to help define the most appropriate statistical and computational methodology approach, depending on the specific nature of the data to be processed.
To improve genetic engineering methodologies, such as genomic editing via the CRISPR/Cas9 system, and the development of innovative preclinical models derived from patients, such as primary tumor cell cultures, 3D organoids and tumoroids (which include both the tumor and stromal component of the patient) and mouse models (PDX), to identify novel therapeutic targets and develop drug combinations potentially capable of interfering with tumor progression and re-educating the tumor microenvironment, with emphasis on oncology drug repositioning already approved in clinical practice; Introduce an omics testing system into routine diagnostics based on the integrated use of genomic, proteomic, metabolomic, and functional tests providing patient-specific multi-level characterization; Develop combined therapeutic approaches using advanced technologies, such as robotic and minimally invasive surgery, radiotherapy, proton therapy, radiosurgery and SBRT, and medical-nuclear therapy; Develop business intelligence models for integrated analysis of clinical and experimental data; New clinical trials
Indicator: Identify potential molecular signatures of response to combination therapeutic approaches, based on molecularly targeted drugs, in different tumor types; Clinical and molecular-genetic characterization of tissues derived from patients at high risk of recurrence, in order to implement precision therapeutic strategies; Develop advanced in vitro and in vivo preclinical models derived from patients primary tumor cell cultures, 3D organoids and tumoroids, PDX to: a) identify new therapeutic targets involved in tumor progression and drug resistance; (b) test new drug combinations; Adopt a diagnostic system based on the integration of omics analyses (genomic, proteomic, metabolomic, and functional assays); Identify a case series of non-small cell lung cancer patients who have a significant dosimetric and radiobiological advantage in treatment with proton therapy; Identify drugs that are potentially transferable to cancer clinical practice to initiate new experimental clinical trials. Communicate/participate in national/international conferences, organize specific intra/extramoenia seminars/meetings. Identify patentable results. Submit applications and obtain competitive Grants.
Result Indicator Program: Participate in congresses and specific intra/extramoenia seminars/conferences. Publications in journals with IF.